Internship - Generating 3D Data for Deep Learning based Lane Detection

Company Description

At Bosch, we shape the future by inventing high-quality technologies and services that spark enthusiasm and enrich people’s lives. Our promise to our associates is rock-solid: we grow together, we enjoy our work, and we inspire each other. Join in and feel the difference.

The Robert Bosch GmbH is looking forward to your application!

Job Description

Lane detection is a fundamental part of driver assistance systems and autonomous driving. In recent years, deep learning based systems have been utilized to estimate the location of lane markings in 3D space. For supervised approaches and to evaluate the performance of such methods, large amounts of high-qualitative video data with corresponding 3D ground truth is required.

• The goal of this internship is to generate 3D lane ground truth using real multi-sensor data to create a large high-quality 3D dataset.
• You will work on real video and LiDAR data as well as implement and deploy methods for multi-sensor based lane detection.
• Furthermore, you will setup a pipeline to automatically generate high-quality 3D ground truth from raw sensor data.
• Last but not least, you will manage and maintain the dataset.

Qualifications

• Education: Master studies in the field of Computer Science, Computer Vision, Robotics, Electrical Engineering or comparable with very good grades
• Personality and Working Practice: strongly committed, self-initiated, motivated and good communication skills
• Experience and Knowledge: understanding important concepts in (3D) computer vision, projective geometry and camera calibration, ideally knowledge in deep learning based detection approaches, very good skills in C++ and Python, experience with image and video data, ideally experience with LiDAR data
• Languages: fluent in English (written and spoken) and ideally good in German

Additional Information

Start: according to prior agreement
Duration: 6 months

Requirement for this internship is the enrollment at university. Please attach a motivation letter, your CV, transcript of records, enrollment certificate, examination regulations and if indicated a valid work and residence permit.

Need further information about the job?
Axel Vogler (Business Department)
+49 711 811 48594

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